During the last couple of years frame-rate up-conversion for LCD televisions has typically been done for lower frame-rates like 50 and 60 frames per second. Recently, the market has been trying to address the sample-and-hold problem of LCD screens. One way of addressing this problem is by up-conversion to higher frame-rates, like 96, 100 or 120 frames per second. Unfortunately, doing up-conversion with a bigger factor also worsens the perceived quality of the video. This is among other factors caused by the fact that for a relatively longer time the interpolated images are shown. The commonly used motion estimation algorithm for frame-rate up-conversion is the 3DRS algorithm, which has been described in G. de Haan and P. W. A. C. Biezen, Sub-pixel motion estimation with 3-D recursive search block-matching, Signal Processing: Image Communication 6, pp. 229.239, 1994 . This algorithm finds a vector for each block in the current frame by minimizing the Sum of Absolute Differences (SAD) for vectors taken from a block-dependent candidate set.
Several up-conversion techniques exist, like static and cascaded median. Details have been described in G. de Haan, Video Processing for multimedia systems, University Press Eindhoven, 2000 . However, these techniques suffer from the so-called halo artifact. In images resulting from motion compensated image rate converters, artifacts are visible at the boundaries of moving objects, where either covering or uncovering of the background occurs. These artifacts are usually referred to as halos. There are two reasons for these halos. The first cause is the resolution of the motion vector field. Usually, the density of the grid at which the motion vectors are available is much less than that of the pixel grid. If, for example, motion vectors are available for blocks of 8×8 pixels then the contours of moving objects can only roughly be approximated at the vector grid, resulting in a blocky halo effect. A second cause is that a motion estimation unit, estimating motion between two successive images of a video sequence, cannot perform well in regions where covering or uncovering occurs, as it is typical for these regions that the background information only occurs in either of the two images.
Methods for performing uncovering-covering detection have been disclosed in US 2006/0072790 A1 . Also see G. de Haan and P. W. A. C. Biezen, Sub-pixel motion estimation with 3-D recursive search block-matching, Signal Processing: Image Communication 6, pp. 229.239, 1994.
Recently several three-frame variants (G. A. Lunter, Occlusion-insensitive motion estimation for segmentation, in Proceedings of the SPIE: Visual Communications and Image Processing, pp. 573.584, January 2002) have been proposed in order to solve occlusion (covering or uncovering) problems. Occlusion occurs in areas of the images which are only visible in some, but not all, of the two or three reference frames. Errors resulting from occlusion are called halo artifacts. These three-frame variants can be used for frame-rate up-conversion using a vector field retimer. Such a vector field retimer is known from WO 2005/027525 A1. These documents disclose an algorithm which has been developed by Philips Research to solve the halo problem without platform constraints. The algorithm consists of two parts, the motion estimator and the temporal up-converter. However, the three-frame estimator and vector field retimer combination is quite expensive to implement.
There is a cheaper halo-reducing algorithm which has been described in patent application US 2006/0072790 A1. Document US 2006/0072790 A1 discloses a method for easily determining an appropriate motion vector in an occlusion region. The method comprises the following steps: computing a model-based motion vector for the pixel on basis of a motion model being determined on basis of a part of a motion vector field of the image; comparing the model-based motion vector with each of the motion vectors of the set of motion vectors; selecting a particular motion vector of the set of motion vectors on basis of the comparing and for assigning the particular motion vector as the background motion vector. However, it turned out to be very likely that this algorithm introduces new artifacts in the video and in practice the algorithm is almost completely turned off. Apart from this, it is also quite expensive to implement.